Spring 2026 InnovAGE Cohort
Brenna Hagan
Recent PhD Graduate at Boston University
Brenna Hagan is advancing non-invasive approaches to detect and monitor Alzheimer’s disease and related dementias. Her work uses techniques like TMS-EEG and neuropsychological assessments to identify early biomarkers, track disease progression, and support more personalized care for aging populations. With strong translational potential, her research could help shape future diagnostic and monitoring tools for clinicians, researchers, and drug developers.
David Hojah
Master's Student at Harvard University
David Hojah is developing Polly NeuroScreen, an AI-powered tool for early detection of Alzheimer’s disease and cognitive decline. The platform combines EEG, speech biomarkers, and wearable data to support clinical screening, monitoring, and longitudinal cognitive tracking. Through Parrots Medical, his work is helping advance more accessible neurotechnology solutions for earlier diagnosis and proactive care.
Gayathri Boopathy
PhD Candidate at UMass Lowell
Gayathri Boopathy is developing AI-driven rehabilitation tools that use augmented reality, computer vision, and human–machine interaction to support aging populations. Her work focuses on AR-based hand tracking, eye-gaze systems, and intelligent motor function assessment in collaboration with physical therapists. By creating accessible, gamified rehabilitation platforms, her research aims to improve recovery, independence, and quality of life for older adults.
Henriette Flore Kenne
PhD Candidate at UMass Lowell
Henriette Flore Kenne is developing secure, speech-based AI systems for early detection of dementia in aging populations. Her work uses privacy-preserving machine learning techniques, including federated learning, adversarial training, and differential privacy, to protect patient data while supporting clinical use. By creating scalable, non-invasive cognitive screening tools, her research aims to improve early diagnosis and bring trustworthy AI into real-world aging care.
Khunza Asma
PhD Candidate at University of South Florida
Khunza Asma is studying the impact of chronic stress on family caregivers of people with Alzheimer’s disease and related dementias. Her work uses large national datasets to examine how caregiver burden, grief, and depression influence cognitive aging, biological risk, and long-term wellbeing. By identifying protective factors and opportunities for earlier support, her research aims to inform equity-focused screening tools, caregiver interventions, and healthcare system applications.
Michael Ajenikoko
PhD Candidate at Kent State University
Michael Ajenikoko is researching metabolic and inflammatory mechanisms involved in Alzheimer’s disease and related neurodegenerative disorders. His work combines experimental neuroscience, advanced microscopy, and computational drug discovery to study microglial lipid metabolism and neuroinflammation in aging brains. By identifying small-molecule therapeutic targets, his research aims to advance new approaches for treating immune and metabolic dysfunction associated with neurodegeneration.
Mohit Kwatra
Postdoctoral Researcher, Medical University of South Carolina
Mohit Kwatra is studying mechanisms of neurodegeneration across the retina–brain axis. His work investigates cellular stress responses, protein mislocalization, mitochondrial and lysosomal dysfunction, and neuroinflammation in diseases including Alzheimer’s disease, Parkinson’s disease, FTD/ALS, and age-related macular degeneration. By connecting fundamental neuroscience with therapeutic development and biomarker discovery, his research aims to advance new translational approaches for age-related neurological conditions.
Md Abu Bakkar Siddik
Postdoctoral Researcher at Texas Tech University
Md Abu Bakkar Siddik is developing aging-focused technologies that connect metabolic disease research with early neurodegenerative detection and intervention. His work identifies branched-chain amino acids as potential early biomarkers for Alzheimer’s disease while also exploring nanoparticle-based drug delivery systems for anti-diabetic therapies. He is currently developing an AI-powered diabetes self-care assistant that uses wearable and continuous glucose monitor data for predictive management, alongside an Alzheimer’s biomarker platform focused on early detection through amino acid profiling. His work aims to advance more proactive, personalized approaches to aging and chronic disease management.
Nayid Jana
PhD Candidate at Washington University in St. Louis School of Medicine
Nayid Jana is developing AI-augmented radiology tools to improve safety monitoring for Alzheimer’s disease treatments. His work focuses on detecting amyloid-related imaging abnormalities, or ARIA, in older adults receiving anti-amyloid therapies. By using AI to reduce diagnostic error and support MRI review workflows, his research aims to make Alzheimer’s treatment monitoring safer, more accurate, and more accessible for aging populations.
Yanjun Dong
PhD Candidate at University at Albany, State University of New York
Yanjun Dong is developing aging-focused care solutions that improve support for older adults, caregivers, and care teams. Her work integrates social, behavioral, and technological factors to strengthen palliative and end-of-life care quality. Drawing on experience with national datasets, randomized controlled trials, and health technology tools such as palliative care support apps and digital advance care planning platforms, her research aims to advance more accessible, compassionate, and practical care innovations for aging populations.
Yuhao (Lauren) Gao
PhD Candidate at Emory University
Yuhao “Lauren” Gao is studying early mechanisms of Alzheimer’s disease using human induced pluripotent stem cell models. Her work explores tau pathology, locus coeruleus dysfunction, and early molecular biomarkers that may support presymptomatic detection and intervention. By connecting disease modeling with translational applications in biomarker discovery, drug screening, and personalized risk assessment, her research aims to help move Alzheimer’s science closer to real-world healthcare solutions.
Ziyuan Huang
Postdoctoral Associate, UMass Chan Medical School
Dr. Ziyuan Huang is developing ADAM-1, an AI-driven framework designed to enhance the understanding and diagnosis of Alzheimer’s disease in aging populations. The platform combines clinical records, microbiome data, and literature-based insights to detect and characterize neurodegenerative conditions. By using large language models and retrieval-augmented generation, his work aims to support earlier detection, disease monitoring, and more personalized clinical decision-making for older adults.
